Buch. Condici�n: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book brings together some of the most impactful researchers in the field of Genetic Programming (GP), each one working on unique and interesting intersections of theoretical development and practical applications of this evolutionary-based machine learning paradigm. Topics of particular interest for this year s book include powerful modeling techniques through GP-based symbolic regression, novel selection mechanisms that help guide the evolutionary process, modular approaches to GP, and applications in cybersecurity, biomedicine and program synthesis, as well as papers by practitioner of GP that focus on usability and real-world results. In summary, readers will get a glimpse of the current state of the art in GP research. 276 pp. Englisch. N� de ref. del art�culo: 9789811984594

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Genetic Programming Theory and Practice XIX

Publicado por Springer, Berlin|Springer Nature Singapore|Springer, 2023

ISBN 10: 981198459X ISBN 13: 9789811984594

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Librería: moluna, Greven, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Condici�n: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book brings together some of the most impactful researchers in the field of Genetic Programming (GP), each one working on unique and interesting intersections of theoretical development and practical applications of this evolutionary-based machine lear. N� de ref. del art�culo: 747116711

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Genetic Programming Theory and Practice XIX

Leonardo Trujillo

Publicado por Springer Nature Singapore, 2023

ISBN 10: 981198459X ISBN 13: 9789811984594

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Librería: AHA-BUCH GmbH, Einbeck, Alemania

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Buch. Condici�n: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book brings together some of the most impactful researchers in the field of Genetic Programming (GP), each one working on unique and interesting intersections of theoretical development and practical applications of this evolutionary-based machine learning paradigm. Topics of particular interest for this year s book include powerful modeling techniques through GP-based symbolic regression, novel selection mechanisms that help guide the evolutionary process, modular approaches to GP, and applications in cybersecurity, biomedicine and program synthesis, as well as papers by practitioner of GP that focus on usability and real-world results. In summary, readers will get a glimpse of the current state of the art in GP research. N� de ref. del art�culo: 9789811984594

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